Asthma: An illustration of health care disparities

Highly sensitive liquid chromatography-mass spectrometry method for the quantitative analysis of mometasone furoate in human plasma: Method validation and application to clinical pharmacokinetic studies

We report the development and the validation of a sensitive liquid chromatography-mass spectrometry (LC-MS/MS) method for mometasone furoate (MF) analysis in human plasma. Plasma samples were processed through liquid-liquid extraction and analyzed using LC-MS/MS operating in positive mode using multiple reaction monitoring of transitions m/z 520.9 → 355.0 and m/z 525.8 → 355.0 for MF and the internal standard (IS), respectively. Separation was achieved at 1.0 mL/min on a C18 column using a gradient elution of mobile phase of 0.05% ammonia in water (phase A) and acetonitrile (phase B). The assay range was 0.250-100 pg/mL and proved to be accurate and precise MF. Normalized recoveries were consistent and reproducible with a coefficient of variation (CV%) value of 6.0. The CV (%) of the IS normalized matrix factor was not observed in normal, lipemic, and hemolyzed plasmas. Dilutions of 1:10 were accurately quantified. A cycle of three freeze and thaw and stabilities at room temperature and on the autosampler were demonstrated. In addition, MF in the presence of indacaterol and glycopyrronium was proven to be stable at -70°C for at least 157 days. The present method was successfully applied to quantify MF in patients receiving MF, indacaterol, and glycopyrronium as a fixed-dose combination.

Machine Learning Approaches to Predict Asthma Exacerbations: A Narrative Review

The implementation of artificial intelligence (AI) and machine learning (ML) techniques in healthcare has garnered significant attention in recent years, especially as a result of their potential to revolutionize personalized medicine. Despite advances in the treatment and management of asthma, a significant proportion of patients continue to suffer acute exacerbations, irrespective of disease severity and therapeutic regimen. The situation is further complicated by the constellation of factors that influence disease activity in a patient with asthma, such as medical history, biomarker phenotype, pulmonary function, level of healthcare access, treatment compliance, comorbidities, personal habits, and environmental conditions. A growing body of work has demonstrated the potential for AI and ML to accurately predict asthma exacerbations while also capturing the entirety of the patient experience. However, application in the clinical setting remains mostly unexplored, and important questions on the strengths and limitations of this technology remain. This review presents an overview of the rapidly evolving landscape of AI and ML integration into asthma management by providing a snapshot of the existing scientific evidence and proposing potential avenues for future applications.

Ensuring equitable access to guideline-based asthma care across the lifespan: Tips and future directions to the successful implementation of the new NAEPP 2020 guidelines, a Work Group Report of the AAAAI Asthma, Cough, Diagnosis, and Treatment Committee

The most recent recommendations from the 2020 National Asthma Education and Prevention Program Update and Global Initiative for Asthma 2021 guide evidence-based clinical decision making. However, given the present state of health disparities by age, income, and race, the equitable implementation and dissemination of these guidelines will be unlikely without further guidance. This work group report reviews the current state of the new asthma guideline implementation; presents updated evidence-based therapeutic options with attention to specific patient populations; and addresses barriers to the implementation of these guidelines in minoritized, historically marginalized, and underresourced communities. Allergists and immunologists can use practical ways to accomplish the goals of improved asthma care access and advanced asthma care across the life span, with specific considerations to historically marginalized populations. Modifiable barriers to guideline implementation include financial barriers, environmental factors, and allergy subspecialty access and care coordination. Various programs to improve access to guideline-based asthma care include community programs, school-based asthma programs, and digital health solutions, with an emphasis on reducing disparities by race.

The efficacy of mometasone furoate for children with asthma: a meta-analysis of randomized controlled trials

Introduction

The influence of mometasone furoate for paediatric asthma remains controversial.

Aim

We conducted a systematic review and meta-analysis to explore the efficacy and safety of mometasone furoate for paediatric asthma.

Material and methods

We have searched PubMed, Embase, Web of science, EBSCO, and Cochrane library databases through October 2019 for randomized controlled trials assessing the effect of mometasone furoate versus placebo for paediatric asthma. This meta-analysis was performed using the random-effects model.

Results

Four RCTs were included in the meta-analysis. Overall, as compared to placebo for paediatric asthma, mometasone furoate is associated with substantially increased predicted forced expiratory volume in 1 s (FEV₁) (mean difference (MD) = 7.53; 95% CI: 7.02–8.04; p < 0.00001), FEV₁ (MD = 0.11; 95% CI: 0.10–0.12; p < 0.00001), and morning peak expiratory flow (AM PEF) (MD = 17.70; 95% CI: 9.91–25.49; p < 0.00001), but demonstrates no obvious effect on pharyngitis (RR = 0.96; 95% CI: 0.59–1.58; p = 0.89), upper respiratory tract infections (RR = 0.73; 95% CI: 0.50–1.05; p = 0.09), or adverse events (RR = 1.05; 95% CI: 0.84–1.31; p = 0.69).

Conclusions

Mometasone furoate may be effective and safe for paediatric asthma.